[Math] Find the orthogonal projection of a function on the set of $L^2$ functions whose integrals are $0$

functional-analysishilbert-spacesprojection

Given $u\in L^2(0, 1)$, find its orthogonal projection on $V =\{v∈L^2(0,1):\int_0^1 v(x)\ dx=0\}$.

For Hilbert spaces it holds a theorem about projections on a closed convex set which states that given a subset $C$ of an Hilber space $H$, $u\in H$, $v\in C$, then $\langle u-v,g-v\rangle\le0,\ \forall\ g\in C$, and $v$ is the orthogonal projecition of $u$ in $C$.

$V$ is closed if every sequence $\{v_n\}\subset V$ converges to an element of $V$, i.e. if $\forall\ \phi(x)\in L^2(0,1):\lim_{n\to+\infty}\int_0^1v_n\phi=\int_0^1v\phi$ (weak convergence).

Take $\phi=\chi_{(0,1)}$, then $\int_0^1v_n\phi=\int_0^1v_n=0$ and $\lim_{n\to+\infty}\int_0^1v_n=\int_0^1v=0$. Then $V$ is closed.

$V$ is convex if every convex combination of two elements of $V$ is still an element of $V$, but I don't know how to check this.

Another theorem about Hilbert spaces says that every Hilbert space splits into the direct sum of any closed subspace and its orthogonal. Statement: given a Hilbert space $X$, a closed subspace $Y$ and the map $p$ which sends any element $x\in X$ to its closest element in $Y$, then $p$ is linear, continuous, and $x-p(x)$ is orthogonal to $Y$. Moreover, if $\{e_1,…,e_n\}$ is an orthonormal basis of $Y$, then $p(x)=\sum_1^n\langle x,e_i\rangle e_i$.

I read that examples of orthonormal basis for $L^2[0,1]$ are $\{e^{2πinx}\}$, for $n$ from $-\infty$ to $+\infty$, and the Legendre polynomials. But these two basis have infinite dimension and so cannot be used to compute $p(x)$, right?

Any hint on how to start the exercise?

Best Answer

Note that $$ V = \left\{ f \in L^2 : \int_0^1 fdx = 0 \right\} = [\{ 1\}]^{\perp}. $$ So $L^2=V\oplus [\{1\}]$. The orthogonal projection of $f$ onto $[\{1\}]$ is $\langle f,1\rangle 1$, and the orthogonal projection of $f$ onto $V$ is $f-\langle f,1\rangle 1$.